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Automatization of ESA Sentinel-3 images query and download

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Sentinel-3 images download

This script automates the per-point search and download of ESA Sentinel-3 images.

An interactive documentation can be found on https://s3-loader.readthedocs.io/

Sources of data:

Requirements

python -m pip install requests requests library https://requests.readthedocs.io/en/master/user/install/

Input:

  • product type
  • dates of acquisition
  • coordinates of a point

See example.py for details

Credentials

DHUS and DAAC require authorization that should be provided in S3_loader/config.py next to the rest of the code:

AUTH = ('username', 'password')
DAAC_API_KEY = 'XXXXXXXX-XXXX-XXXX-XXXX-XXXXXXXXXXXX'

DAAC_API_KEY can be generated on https://ladsweb.modaps.eosdis.nasa.gov/profile/#app-keys. ESA Sentinel-3 End User License Agreement should be accepted by ticking "Yes, I Agree to ESA Sentinel-3 End User License Agreement." at the end of the page https://urs.earthdata.nasa.gov/profile/edit

User steps:

  1. Query for product names and unique identifiers (uuid)
  2. Download of products:
    • online products - direct parallel download from Copernicus Open Access Hub
    • offline products (Long term archive, LTA) - from LAADS DAAC (if available)
  3. Extract pixels from loaded images:
  4. Database extras:
    • mark offline (LTA) products
    • mark products available at DAAC
    • set "loaded" to avoid double download

Output:

  • SQLite database file with tables:
    1. site: coordinates
      • to keep track of "single coordinates - single database"
    2. products: name, uuid, size:
      • individual table for each product type
  • Downloaded products
  • Text files with extracted pixels

OLCI level-1: Google Earth Engine alternative

Google Earth Engine can do everything that this package does [pixel extraction], but there is only OLCI level-1 collection available https://code.earthengine.google.com/61fe01512385e06b5bc3f65f78bef692?noload=true

Recommendations

The code was used in (Prikaziuk, Yang en Van der Tol, 2021) https://doi.org/10.3390/rs13061098

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